Movatterモバイル変換


[0]ホーム

URL:


CN117597911B - Method and system for real-time reporting of metrics to replaceable agents in a full-spectrum contact center - Google Patents

Method and system for real-time reporting of metrics to replaceable agents in a full-spectrum contact center
Download PDF

Info

Publication number
CN117597911B
CN117597911BCN202280047104.0ACN202280047104ACN117597911BCN 117597911 BCN117597911 BCN 117597911BCN 202280047104 ACN202280047104 ACN 202280047104ACN 117597911 BCN117597911 BCN 117597911B
Authority
CN
China
Prior art keywords
call
service request
request call
customer
service
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202280047104.0A
Other languages
Chinese (zh)
Other versions
CN117597911A (en
Inventor
R·埃达马达卡
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
JPMorgan Chase Bank NA
Original Assignee
JPMorgan Chase Bank NA
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by JPMorgan Chase Bank NAfiledCriticalJPMorgan Chase Bank NA
Publication of CN117597911ApublicationCriticalpatent/CN117597911A/en
Application grantedgrantedCritical
Publication of CN117597911BpublicationCriticalpatent/CN117597911B/en
Activelegal-statusCriticalCurrent
Anticipated expirationlegal-statusCritical

Links

Classifications

Landscapes

Abstract

A method and system for reporting metrics related to customer calls for an alternative plurality of agents in a contact center environment that utilize a plurality of service applications is provided. The method includes receiving a service request call from a client, determining an application available to respond to the service request call from a predetermined plurality of applications, monitoring the service request call to obtain information related to a call time and an event occurring during the call, determining call-specific metrics, such as hold time, number of transfers, and/or idle time, based on the information obtained during the monitoring when the service request call is completed, and reporting the metrics to a repository. Additional metrics specific to the agent assigned to handle the call may also be determined.

Description

Method and system for reporting indicators in real time to replaceable agents in full frequency contact centers
Cross Reference to Related Applications
The present application claims priority from U.S. application Ser. No. 17/363,984, filed on 6/30 of 2021, incorporated herein by reference in its entirety.
Technical Field
The present technology relates generally to methods and systems for reporting metrics related to customer calls, and more particularly to methods and systems for reporting metrics related to customer calls with alternative agents for multiple service applications in a contact center environment.
Background
Customer service is an important aspect of business operation for large corporate organizations that own many customers. Customers often wish to process service requests in a timely and accurate manner, and if a corporate organization fails to provide such customer service, the reputation of the organization may be negatively impacted.
Many client service requests are made online over the internet. For such requests, a corporate organization may utilize a contact center that facilitates the provision of various service applications from different parts of the organization. However, due to the diversity of applications and the scale of overall operations, software developers may experience difficulties in integrating newly developed applications with other portions of the software suite that serve the contact center.
In addition, at the contact center, an alternative agent will answer calls from multiple business line service applications and switch services to the customer for different service applications in the same call. When a professional handles different service applications during the same call to help customers, tracking metrics about the average processing time, average talk time, etc. of the professional is also a challenge for a particular type of service application, which is one of the many alternative service applications that the professional handles during the same call. In contrast, typical contact center reporting solutions rely on routing-related information to calculate proxy and queue statistics, and these traditional reporting solutions rely only on one type of service application that is used to assist customers that matches the type of call identified by the routing system. When another type of service application is needed, the professional will switch the client to another virtual queue of professionals with different skills. To reduce the number of transfers required and enhance the customer experience, alternative contact center professionals can handle different types of service requests that match the customer's consultation intents, and they can use more than one service application.
Accordingly, there is a need for methods and systems for alternative agents in a contact center environment that utilize multiple service applications to report metrics related to customer calls.
Disclosure of Invention
The present disclosure, by one or more of its various aspects, embodiments, and/or specific features or sub-components, is directed to various systems, servers, devices, methods, media, programs, and platforms for reporting metrics related to customer calls in a contact center environment utilizing alternative agents for multiple service applications.
In accordance with one aspect of the present disclosure, a method is provided for reporting metrics related to a customer call in a contact center environment using an alternative agent of a plurality of service applications. The method is implemented by at least one processor. The method includes receiving, by at least one processor, a service request call from a first customer, determining, by the at least one processor, at least one application from a predetermined plurality of applications available to respond to the service request call, monitoring, by the at least one processor, the service request call for information related to a time of the service request call, at least one event occurring during the service request call, and at least one output of the at least one application, determining, by the at least one processor, at least one call-specific indicator based on the information obtained as a result of the monitoring when the service request call is completed, and reporting, by the at least one processor, each of the determined at least one call-specific indicators to a predetermined destination.
The at least one call specific indicator may include at least one of hold time, talk time, average processing time, call intention, call processing, speed of answer, number of dropped calls, number of processed calls, average post-call working time, percentage of calls held, average duration of calls held, percentage of post-call working of average processing time, number and percentage of calls forwarded, number and percentage of conference calls, percentage of forwarded or conference calls combinations, percentage of service levels, number of forwarded, idle time, call count, type of service application for each service request by each team's professionals and team leader during the call, and number of call records.
The at least one call-specific indicator may also include a sum of service levels over a day, an average processing time, an average answering speed, a number of calls provided and a number of calls processed, a sum and/or an average of indicators over a predetermined interval (e.g., 30 minutes, 8 hours per day, one week, or one month). Each call and interval report has a goal and threshold that is also calculated in real-time and displayed to professionals and team leaders to monitor and take appropriate action.
The method may also include generating trends from such aggregations, which are then used for labor management and prediction.
The method may further include identifying an agent assigned to handle the service request call and calculating at least one agent-specific indicator based on the determined at least one call-specific indicator and previously stored agent-specific indicator data.
The method may further include capturing at least one metadata item associated with the service request call. The at least one metadata item may include at least one of telephony data, subscriber profile data associated with the identified agent, an identification of each of the at least one application, and information associated with whether the identified agent performed a search function during the service request call.
The method may further include displaying a user interface on a display associated with the identified agent, the user interface including information related to the service request call and information related to a historical interaction sequence corresponding to the first customer.
The at least one application may include a first application operable to respond to a first aspect of the service request call and at least a second application operable to respond to a second aspect of the service request call.
The at least one call-specific indicator may comprise a first call-specific indicator related to a first aspect of the service request call and at least a second call-specific indicator related to a second aspect of the service request call.
The method may further include monitoring and reporting using a container application designed to facilitate interaction between respective ones of the predetermined plurality of applications.
In addition, the container application may display the customer itinerary in the same call as the customer that the professional assisted, and more than one application matches the customer's intent or consultation with the processing of each application and links it to the historical interaction sequence of the customer itinerary when the customer's intent was achieved.
The at least one call-specific indicator may also include an amount of time spent within the service application of the business transaction and actions taken. These metrics, as well as other data including the customer's device, first use cases, etc., may be collected as part of a clickstream event that may be sent to a post-analysis big data system with business insight visualization.
According to another exemplary embodiment, a computing device for reporting metrics related to a customer call is presented. The computing device includes a processor, a memory, and a communication interface coupled to each of the processor and the memory. The processor is configured to receive a service request call from a first customer via a communication interface, determine at least one application from a predetermined plurality of applications available to respond to the service request call, monitor the service request call for information related to a time of the service request call, at least one event occurring during the service request call, and at least one output of the at least one application, determine at least one call specific indicator based on the information obtained as a result of the monitoring when the service request call is completed, and report each of the determined at least one call specific indicators to a predetermined destination.
The at least one call specific indicator may include at least one of hold time, talk time, average processing time, call intention, call processing, speed of answer, number of dropped calls, number of processed calls, average post-call working time, percentage of calls held, average duration of calls held, percentage of post-call working of average processing time, number and percentage of calls forwarded, number and percentage of conference calls, percentage of forwarded or conference calls combinations, percentage of service levels, number of forwarded, idle time, call count, type of service application for each service request by each team's professionals and team leader during the call, and number of call records.
The processor may be further configured to identify an agent assigned to handle the service request call and calculate at least one agent-specific indicator based on the determined at least one call-specific indicator and previously stored agent-specific indicator data.
The processor may be further configured to capture at least one metadata item related to the service request call. The at least one metadata item may include at least one of telephony data, subscriber profile data associated with the identified agent, an identification of each of the at least one application, and information associated with whether the identified agent performed a search function during the service request call.
The processor may be further configured to display a user interface on a display associated with the identified agent, the user interface including information related to the service request call and information related to a historical interaction sequence corresponding to the first customer.
The at least one application may include a first application operable to respond to a first aspect of the service request call and at least a second application operable to respond to a second aspect of the service request call.
The at least one call-specific indicator may comprise a first call-specific indicator related to a first aspect of the service request call and at least a second call-specific indicator related to a second aspect of the service request call.
The processor may also be configured to monitor and report using container applications designed to facilitate interactions between respective ones of a predetermined plurality of applications.
The container application may pass the reporting metrics collected for each set of applications to the contact center reporting system and append it as metadata for identifying records and analysis and use it as metadata when the customer is switched or contacted the company again to enrich the customer's experience.
According to yet another exemplary embodiment, a non-transitory computer-readable storage medium storing instructions for reporting metrics related to a customer call is presented. The storage medium includes executable code that, when executed by the processor, causes the processor to receive a service request call from a first client, determine at least one application from a predetermined plurality of applications available to respond to the service request call, monitor the service request call for information related to a time of the service request call, at least one event occurring during the service request, and at least one output of the at least one application, determine at least one call specific indicator based on a result of the monitoring when the service request call is completed, and report each of the determined at least one call specific indicators to a predetermined destination.
The executable code may be further configured to cause the processor to identify an agent assigned to process the service request call and calculate at least one agent-specific indicator based on the determined at least one call-specific indicator and previously stored agent-specific indicator data.
The executable code may be further configured to cause the processor to display a user interface on a display associated with the identified agent, the user interface including information related to the service request call and information related to a historical interaction sequence corresponding to the first customer.
The at least one application may include a first application operable to respond to a first aspect of a service request call and at least a second application operable to respond to a second aspect of a service request call.
Drawings
In the following detailed description, the disclosure is further described by way of non-limiting examples of preferred embodiments of the disclosure with reference to the several figures of the drawings, in which like reference numerals refer to like elements throughout the several views.
FIG. 1 illustrates an exemplary computer system.
Fig. 2 illustrates an example diagram of a network environment.
Fig. 3 illustrates an exemplary system for implementing a method for reporting metrics related to a customer call with an alternative agent of a plurality of service applications in a contact center environment.
Fig. 4 is a flow chart of an exemplary process for implementing a method for reporting metrics related to a customer call by an alternative agent utilizing multiple service applications in a contact center environment.
Fig. 5 is an architecture diagram of a system for implementing a method for reporting metrics related to a customer call with an alternative agent of a plurality of service applications in a contact center environment, according to an exemplary embodiment.
Detailed Description
The disclosure is directed to one or more advantages particularly described above and below by way of one or more of its various aspects, embodiments, and/or specific features or sub-components.
Examples may also be embodied as one or more non-transitory computer-readable media having instructions stored thereon for one or more aspects of the present technology as described and illustrated herein by way of example. The instructions in some examples include executable code that, when executed by one or more processors, cause the processors to perform the steps necessary to implement the methods in the examples of the technology described and illustrated herein.
FIG. 1 is an exemplary system for use in accordance with embodiments described herein. The system 100 is generally shown and may include a computer system 102, which is generally indicated.
The computer system 102 may include a set of instructions that are executable to cause the computer system 102 to perform any one or more of the methods or computer-based functions disclosed herein, alone or in combination with other described devices. The computer system 102 may operate as a standalone device or may be connected to other systems or peripheral devices. For example, computer system 102 may include or be included in any one or more computers, servers, systems, communication networks, or cloud environments. Further, the instructions may be executed in such a cloud-based computing environment.
In a networked deployment, the computer system 102 may operate in the capacity of a server, or as a client user computer in a server-client user network environment, a client user computer in a cloud computing environment, or a peer computer system in a peer-to-peer (or distributed) network environment. Computer system 102, or portions thereof, may be implemented as or incorporated into a variety of devices, such as a personal computer, tablet computer, set-top box, personal digital assistant, mobile device, palmtop computer, laptop computer, desktop computer, communication device, wireless smart phone, personal trusted device, wearable device, global Positioning Satellite (GPS) device, network device, or any other machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while a single computer system 102 is illustrated, additional embodiments may include any collection of systems or subsystems that individually or jointly execute instructions or perform functions. The term "system" shall be taken throughout the present disclosure to include any collection of systems or subsystems that individually or jointly execute one or more sets of instructions to perform one or more computer functions.
As shown in fig. 1, computer system 102 may include at least one processor 104. The processor 104 is tangible and non-transitory. As used herein, the term "non-transitory" should not be construed as a permanent feature of a state, but rather a feature that a state will last for a period of time. The term "non-transitory" specifically denies transitory features such as the features of a particular carrier or signal or other form of carrier or signal that only exists anywhere at any time. The processor 104 is an article of manufacture and/or a machine component. The processor 104 is configured to execute software instructions in order to perform the functions as described in the various embodiments herein. The processor 104 may be a general purpose processor or may be part of an Application Specific Integrated Circuit (ASIC). The processor 104 may also be a microprocessor, microcomputer, processor chip, controller, microcontroller, digital Signal Processor (DSP), state machine, or programmable logic device. The processor 104 may also be logic circuitry including a Programmable Gate Array (PGA), such as a Field Programmable Gate Array (FPGA), or another type of circuit including discrete gate and/or transistor logic. The processor 104 may be a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), or both. Further, any of the processors described herein may include multiple processors, parallel processors, or both. Multiple processors may be included in or coupled to a single device or multiple devices.
The computer system 102 may also include a computer memory 106. The computer memory 106 may include static memory in communication, dynamic memory, or both. The memory described herein is a tangible storage medium that can store data as well as executable instructions and is non-transitory during the time that the instructions are stored therein. Also, as used herein, the term "non-transitory" should not be construed as a permanent feature of a state, but rather a feature that a state will last for a period of time. The term "non-transitory" specifically denies transitory features such as the features of a particular carrier or signal or other form of carrier or signal that only exists anywhere at any time. The memory is an article of manufacture and/or a machine component. The memory described herein is a computer-readable medium from which a computer can read data and executable instructions. The memory as described herein may be Random Access Memory (RAM), read Only Memory (ROM), flash memory, electrically Programmable Read Only Memory (EPROM), electrically Erasable Programmable Read Only Memory (EEPROM), registers, hard disk, cache, a removable disk, magnetic tape, a compact disc read only memory (CD-ROM), a Digital Versatile Disc (DVD), a floppy disk, a blu-ray disc, or any other form of storage medium known in the art. The memory may be volatile or nonvolatile, secure and/or encrypted, unsecure and/or unencrypted. Of course, the computer memory 106 may comprise any combination of memories or a single memory.
Computer system 102 may also include a display 108, such as a Liquid Crystal Display (LCD), an Organic Light Emitting Diode (OLED), a flat panel display, a solid state display, a Cathode Ray Tube (CRT), a plasma display, or any other type of display, examples of which are well known to those of skill in the art.
The computer system 102 may also include at least one input device 110, such as a keyboard, a touch-sensitive input screen or tablet, voice input, a mouse, a remote control device with a wireless keyboard, a microphone coupled to a speech recognition engine, a camera such as a video camera or still camera, a cursor control device, a Global Positioning System (GPS) device, an altimeter, a gyroscope, an accelerometer, a proximity sensor, or any combination thereof. Those skilled in the art will appreciate that various embodiments of the computer system 102 may include a plurality of input devices 110. Moreover, those skilled in the art will also appreciate that the above-listed exemplary input devices 110 are not meant to be exhaustive, and that the computer system 102 may include any additional or alternative input devices 110.
The computer system 102 may also include a media reader 112, the media reader 112 being configured to read any one or more sets of instructions, e.g., software, from any of the memories described herein. The instructions, when executed by a processor, may be used to perform one or more of the methods and processes described herein. In particular embodiments, the instructions may reside, completely or at least partially, within the memory 106, the media reader 112, and/or the processor 110 during execution thereof by the computer system 102.
Further, computer system 102 may include any additional devices, components, parts, peripherals, hardware, software, or any combination thereof, which are well known and understood to be included in computer systems, such as, but not limited to, network interface 114 and output device 116. The output device 116 may be, but is not limited to, a speaker, an audio output, a video output, a remote control output, a printer, or any combination thereof.
The various components in computer system 102 may be interconnected and communicate by a bus 118 or other communication link. As shown in fig. 1, the components may be interconnected and communicate by an internal bus. However, it will be appreciated by those skilled in the art that any of the components may also be connected by an expansion bus. Further, bus 118 may enable communication via any standard or other specification known and understood, such as, but not limited to, peripheral component interconnect express, parallel advanced technology attachment, serial advanced technology attachment, and the like.
Computer system 102 may communicate with one or more additional computer devices 120 via a network 122. The network 122 may be, but is not limited to, a local area network, a wide area network, the internet, a telephone network, a short range network, or any other network known and understood in the art. The short-range network may include, for example, bluetooth, zigbee, infrared, near field communication, ultra wideband, or any combination thereof. Those skilled in the art will appreciate that additional networks 122, which are known and understood, may additionally or alternatively be used, and that the exemplary network 122 is not limiting or exhaustive. Further, although network 122 is shown in fig. 1 as a wireless network, those skilled in the art will appreciate that network 122 may also be a wired network.
The additional computer device 120 is illustrated in fig. 1 as a personal computer. However, those skilled in the art will appreciate that in alternative embodiments of the application, computer device 120 may be a laptop computer, a tablet computer, a personal digital assistant, a mobile device, a palmtop computer, a desktop computer, a communication device, a wireless telephone, a personal trusted device, a network device, a server, or any other device capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that device. Of course, those skilled in the art will appreciate that the devices listed above are merely exemplary devices, and that device 120 may be any additional device or apparatus known and understood in the art without departing from the scope of the present application. For example, the computer device 120 may be the same as or similar to the computer system 102. Furthermore, it will also be appreciated by those skilled in the art that the apparatus may be any combination of individual apparatuses and devices.
Of course, those skilled in the art will appreciate that the above-listed components of computer system 102 are meant to be exemplary only and are not intended to be exhaustive and/or inclusive. Moreover, the examples of components listed above are also meant to be exemplary and are not meant to be exhaustive and/or inclusive as such.
According to various embodiments of the present disclosure, the methods described herein may be implemented using a hardware computer system executing a software program. Further, in an exemplary, non-limiting embodiment, implementations can include distributed processing, component/object distributed processing, and parallel processing. The virtual computer system processing may be configured to implement one or more of the methods or functions as described herein, and the processors described herein may be used to support a virtual processing environment.
As described herein, in various embodiments, an optimization method and system for reporting metrics related to customer calls with alternative agents of multiple service applications in a contact center environment are provided.
Referring to fig. 2, a schematic diagram of an exemplary network environment 200 implementing a method for reporting metrics related to customer calls with an alternative agent of a plurality of service applications in a contact center environment is shown. In an exemplary embodiment, the method may be performed on any networked computer platform, such as a Personal Computer (PC).
A method for reporting metrics related to a customer call in a contact center environment using an alternative agent of a plurality of service applications may be implemented by a Service Application Call Metrics Reporting (SACMR) device 202. SACMR the device 202 may be the same as or similar to the computer system 102 described with respect to fig. 1. SACMR device 202 may store one or more applications that may include executable instructions that, when executed by SACMR device 202, cause SACMR device 202 to perform actions such as sending, receiving, or otherwise processing network messages, and perform other actions as described and illustrated below with reference to the figures. An application may be implemented as a module or component of other applications. Further, applications may be implemented as operating system extensions, modules, plug-ins, and the like.
Further, applications may run in a cloud-based computing environment. The application may be executed within or as a virtual machine or virtual server managed in a cloud-based computing environment. Further, applications, and even SACMR devices 202 themselves, may reside in virtual servers running in a cloud-based computing environment rather than being bound to one or more specific physical network computing devices. Further, the application may run in one or more Virtual Machines (VMs) executing on SACMR devices 202. Further, in one or more embodiments of the technology, the virtual machine running on SACMR device 202 may be managed or supervised by a hypervisor.
In the network environment 200 of fig. 2, SACMR devices 202 are coupled to a plurality of server devices 204 (1) -204 (n) carrying a plurality of databases 206 (1) -206 (n) via a communication network 210, and are also coupled to a plurality of client devices 208 (1) -208 (n). SACMR a communication interface of device 202, such as network interface 114 of computer system 102 of fig. 1, is operable to couple and communicate between SACMR device 204, server devices 204 (1) -204 (n), and/or client devices 208 (1) -208 (n), all coupled together by a communication network 210, although other types and/or numbers of communication networks or systems having other types and/or numbers of connections and/or configurations to other devices and/or elements may also be used.
Communication network 210 may be the same or similar to network 122 described with respect to fig. 1, but SACMR devices 202, server devices 204 (1) -204 (n), and/or client devices 208 (1) -218 (n) may be coupled together by other topologies. In addition, network environment 200 may include other network devices, such as one or more routers and/or switches, which are well known in the art and therefore will not be described herein. The techniques provide a number of advantages, including methods, non-transitory computer-readable media, and SACMR devices that effectively implement methods for reporting metrics related to customer calls with alternative agents for multiple service applications in a contact center environment.
By way of example only, the communication network 210 may include a Local Area Network (LAN) or a Wide Area Network (WAN), and may use Ethernet TCP/IP and industry standard protocols, but other types and/or numbers of protocols and/or communication networks may also be used. The communication network 210 in this example may employ any suitable interface mechanism and network communication technology including, for example, any suitable form of long-distance communication traffic (e.g., voice, modem, etc.), public Switched Telephone Network (PSTN), ethernet-based Packet Data Network (PDN), combinations thereof, and the like.
SACMR device 202 may be a stand-alone device or may be integrated with one or more other devices or apparatuses, such as one or more of server devices 204 (1) -204 (n). In one particular example, SACMR device 202 may include or be carried by one of server devices 204 (1) -204 (n), and other devices may also be present. Further, one or more of SACMR devices 202 may be in the same communication network or in different communication networks, including, for example, one or more public, private, or cloud networks, etc.
The plurality of server devices 204 (1) -204 (n) may be the same as or similar to the computer system 102 or computer device 120 described with respect to fig. 1, including any feature or any combination of features described with respect to fig. 1. For example, any of server devices 204 (1) -204 (n) may include, among other features, one or more processors, memory, and communication interfaces coupled together by a bus or other communication link, although other numbers and/or types of network devices may be used. The server devices 204 (1) -204 (n) in this example may process requests received from SACMR devices 202 via the communication network 210 according to, for example, HTTP-based and/or JavaScript object notation (JSON) protocols, although other protocols may be used.
Server devices 204 (1) -204 (n) may be hardware or software or may represent a system having multiple servers in a pool, which may include an internal network or an external network. Server devices 204 (1) -204 (n) carry databases 206 (1) -206 (n) configured to store data related to agent-specific call service indicators and customer-specific call services.
Although server devices 204 (1) -204 (n) are illustrated as a single device, one or more actions of each server device 204 (1) -204 (n) may be distributed to one or more different network computing devices that together comprise one or more of server devices 204 (1) -204 (n). Further, the server devices 204 (1) -204 (n) are not limited to a particular configuration. Thus, the server devices 204 (1) -204 (n) may contain multiple network computing devices that operate using a master/slave approach, whereby one of the network computing devices of the server devices 204 (1) -204 (n) operates to manage and/or otherwise coordinate the operation of the other network computing devices.
Server devices 204 (1) -204 (n) may operate as multiple network computing devices within, for example, a cluster architecture, a peer-to-peer architecture, a virtual machine, or a cloud architecture. Thus, the techniques disclosed herein should not be construed as limited to a single environment, and other configurations and architectures are also contemplated.
The plurality of client devices 208 (1) -208 (n) may also be the same as or similar to the computer system 102 or computer device 120 described with respect to fig. 1, including any feature or any combination of features described with respect to fig. 1. For example, client devices 208 (1) -208 (n) in this example may include any type of computing device that may interact with SACMR devices 202 via communication network 210. Thus, client devices 208 (1) -208 (n) may be mobile computing devices, desktop computing devices, laptop computing devices, tablet computing devices, virtual machines (including cloud-based computers), and the like, that carry applications such as chat, email, or voice-to-text. In an exemplary embodiment, at least one client device 208 is a wireless mobile communication device, i.e., a smartphone.
Client devices 208 (1) -208 (n) may run interface applications, such as standard web browsers or stand-alone client applications, which may provide interfaces to communicate with SACMR devices 202 via communication network 210 in order to communicate user requests and information. Client devices 208 (1) -208 (n) may include, among other features, a display device (e.g., a display screen or touch screen) and/or an input device (e.g., a keyboard).
Although the exemplary network environment 200 is described and illustrated herein with SACMR devices 202, server devices 204 (1) -204 (n), client devices 208 (1) -208 (n), and communication network 210, other types and/or numbers of systems, devices, components, and/or elements in other topologies may be used. It should be understood that the systems in the examples described herein are for illustrative purposes as many variations of the specific hardware and software used to implement the examples are possible, as will be appreciated by those skilled in the relevant art(s).
One or more devices described in network environment 200, such as SACMR devices 202, server devices 204 (1) -204 (n), or client devices 208 (1) -208 (n), may be configured to run as virtual instances on the same physical machine. In other words, one or more of SACMR devices 202, server devices 204 (1) -204 (n), or client devices 208 (1) -208 (n) may operate on the same physical device, rather than as separate devices communicating over communication network 210. Further, there may be more or fewer SACMR devices 202, server devices 204 (1) -204 (n), or client devices 208 (1) -208 (n) than shown in fig. 2.
Further, in any example, two or more computing systems or devices may replace any one system or device. Thus, the principles and advantages of distributed processing, such as redundancy and replication, may also be implemented as needed to improve the robustness and performance of the devices and systems in the examples. These examples may also be implemented on a computer system that extends over any suitable network using any suitable interface mechanism and communication traffic technology, including, by way of example only, any suitable form of long distance communication traffic (e.g., voice, modem, etc.), wireless communication traffic networks, cellular communication traffic networks, packet Data Networks (PDNs), the internet, intranets, and combinations thereof.
SACMR device 202 is depicted and described in fig. 3 as including service application call metrics reporting module 302, but may include, for example, other rules, policies, modules, databases, or applications. As described below, contact center service structure container module 302 is configured to implement a method for reporting metrics related to customer calls with an alternative agent of a plurality of service applications in a contact center environment.
An exemplary process 300 for implementing a mechanism for reporting metrics related to a customer call for an alternative agent utilizing multiple service applications in a contact center environment using the network environment of fig. 2 is shown as being performed in fig. 3. Specifically, the first client device 208 (1) and the second client device 208 (2) are shown in communication with SACMR devices 202. In this regard, the first client device 208 (1) and the second client device 208 (2) may be "clients" of SACMR devices 202, and are described as such herein. However, it is to be appreciated and understood that the first client device 208 (1) and/or the second client device 208 (2) need not be "clients" of SACMR devices 202, or any entity described in association therewith. Any additional or alternative relationship may or may not exist between either or both of the first client device 208 (1) and the second client device 208 (2) and SACMR devices 202.
In addition, SACMR devices 202 are shown as having access to agent-specific call metrics data store 206 (1) and customer-specific call services database 206 (2). The service application call metrics reporting module 302 may be configured to access these databases to implement a method for reporting metrics related to customer calls with alternative agents of multiple service applications in a contact center environment.
The first client device 208 (1) may be, for example, a smart phone. Of course, the first client device 208 (1) may be any of the additional devices described herein. The second client device 208 (2) may be, for example, a Personal Computer (PC). Of course, the second client device 208 (2) may be any of the additional devices described herein.
The process may be performed via a communication network 210, which communication network 210 may include a plurality of networks as described above. For example, in one exemplary embodiment, either or both of the first client device 208 (1) and the second client device 208 (2) may communicate with SACMR devices 202 via broadband or cellular communications. Of course, these embodiments are merely exemplary and are not intended to be limiting or exhaustive.
Once the service application call metrics reporting module 302 is activated, it performs a process for reporting metrics related to customer calls with an alternative agent of multiple service applications in a contact center environment. An exemplary process for an alternative agent reporting metrics related to a customer call using multiple service applications in a contact center environment is generally shown in flow chart 400 of fig. 4.
In the process 400 of fig. 4, the service application call indicator reporting module 302 receives a service request call from a customer, step S402. In step S404, the call is assigned to an agent, and the service application call indicator reporting module 302 determines the identity of the agent. In an exemplary embodiment, the service application call indicator reporting module 302 may display a user interface at a workstation associated with the agent and may include information related to the call and the customer, for example, information related to a historical interaction sequence with the customer. Such information is commonly referred to as "customer itineraries".
In step S406, the service application call indicator reporting module 302 determines which of the available software applications will facilitate responding to various aspects of the customer' S service request. In an exemplary embodiment, the contact center may use a container application (container application) configured to facilitate interactions between multiple applications for various functions designed to handle customer service consultation. In this regard, the service application call indicator reporting module 302 may select one or more applications integrated into the container application for processing a particular service request made by a customer. Alternatively, the agent handling the call may simply select which applications are most helpful. Importantly, in many cases, customer service request calls may place multiple requests and/or may include several aspects, preferably handled by using different applications.
In step S408, the service application call indicator reporting module 302 monitors the call. In an exemplary embodiment, calls are monitored for time, events, and output of the application for handling each individual aspect of the service request. For example, the start time and end time of the call may be recorded, and any other time-related aspect, such as hold time and/or idle time, may be recorded. As another example, if the client transitions from a first agent to a second agent, the event may be logged. Other events and/or application outputs may vary greatly based on the specifics of the service request.
In step S410, the service application call indicator reporting module 302 determines a set of indicators associated with the customer service request call. The metrics may include call-specific metrics such as hold time, idle time, number of transfers, call count, and/or call records. The metrics may also include agent specific metrics that may be calculated with reference to previously stored agent specific data. For example, as determined in step S408, an agent-specific Average Hold Time (AHT) may be calculated by combining previously stored agent-specific AHT data with the hold time of the current call. In an exemplary embodiment, the metrics may also include metadata items related to the service request call, such as telephone data, user profile data related to the agent, identification of the application used to respond to the service request, and whether a search function was performed during the call.
In step S412, the service application call indicator reporting module 302 reports the indicator to the call center central repository so that all interested parties in the call center environment can access the indicator. In an exemplary embodiment, the container application may be used to route metrics to the appropriate destination.
Fig. 5 is an architecture diagram 500 of a system for implementing a method for reporting metrics related to a customer call with an alternative agent of a plurality of service applications in a contact center environment, according to an exemplary embodiment. As shown in architecture diagram 500, an interactive services architecture (ISF) container technology prototype implements alternative reporting through a container, where the container includes a plurality of service applications.
In an exemplary embodiment, during the same call (1 a), the professional assists the customer with multiple service applications, also referred to herein as micro-front ends, including (2 a) and (2 b) retail accounts, (3) credit card consultation, and (4) requests related to automotive loans. The index is continuously updated in (1 b). The different products may be pushed out by a hot link from one micro front end to another or with (5) an overall view micro front end. The container monitors the activity of each micro front end and sends the raw data to the ISF through the network socket. The web socket notification passes the service application event from the container to the ISF and the computed metrics from the ISF to the container.
The metrics for each service application used during the call may include any one or more of hold time, talk time, average processing time, call intent, call processing, speed of answer, number of dropped calls, number of calls processed, average post-call working time, percentage of calls held, average duration of calls held, post-call working percentage of average processing time, number and percentage of calls forwarded, number and percentage of conference calls, percentage of forwarded or conference call combinations, percentage of service levels, number of forwarded, idle time, call count, type of service application for each service request during the call for each team's professionals and team leaders, and number of call records.
The interval report may include any one or more of the total daily of service level, average processing time, average speed of answer, number of calls provided and processed, total sum and/or average of indicators over an interval (e.g., 30 minutes or 8 hours, one week or one month), targets and thresholds are also calculated in real time and displayed to professionals and team leaders for monitoring and appropriate action.
Trend ISFs can generate trends from this aggregation, which can then be used for labor management and prediction.
Interfaces with other systems-data lakes, traditional reporting systems, and analytics systems-index data and click stream data (i.e., first user access, device type, operating system, time spent, business transaction details, time spent per click stream architecture) are sent to the data lakes for historical analysis, business insight, quality, and dashboard production, as well as to traditional contact center reporting systems. Customer itinerary visualization may also be drawn by combining current calls and historical interactions.
Thus, with this technique, an optimization process is provided for reporting metrics related to customer calls in a contact center environment using alternative agents for multiple service applications.
While the invention has been described with reference to several exemplary embodiments, it is understood that the words which have been used are words of description and illustration, rather than words of limitation. Changes may be made, within the purview of the appended claims, as presently stated and as amended, without departing from the scope and spirit of the various aspects of the present disclosure. Although the invention has been described with reference to particular means, materials and embodiments, the invention is not intended to be limited to the particulars disclosed, but rather extends to all functionally equivalent structures, methods and uses, such as are within the scope of the appended claims.
For example, while a computer-readable medium may be described as a single medium, the term "computer-readable medium" includes a single medium or multiple media, such as a centralized or distributed database, and/or associated caches and servers that store the one or more sets of instructions. The term "computer-readable medium" shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor or that cause a computer system to perform any one or more of the embodiments disclosed herein.
The computer-readable medium may include one or more non-transitory computer-readable media and/or include one or more transitory computer-readable media. In certain non-limiting, exemplary embodiments, the computer readable medium can comprise a solid state memory, such as a memory card or other package housing one or more non-volatile read-only memories. Furthermore, the computer readable medium may be random access memory or other volatile rewritable memory. Furthermore, the computer-readable medium may include magneto-optical or optical media, such as magnetic disks or tape or other storage devices, to capture carrier signals, such as signals transmitted over transmission media. Accordingly, the disclosure is considered to include any computer-readable medium or other equivalent and successor media, in which data or instructions may be stored.
Although the application describes particular embodiments of computer programs or code segments that can be implemented in a computer readable medium, it should be understood that special purpose hardware implementations, such as application specific integrated circuits, programmable logic arrays, and other hardware devices, can be constructed to implement one or more of the embodiments described herein. Applications that may include the various embodiments set forth herein may broadly include a variety of electronic and computer systems. Accordingly, the present application may comprise software, firmware, and hardware implementations, or combinations thereof. Nothing in this application should be construed as being implemented or realized in software only and not in hardware.
Although the present specification describes components and functions that may be implemented in a particular embodiment with reference to particular standards and protocols, the disclosure is not limited to such standards and protocols. Such standards are periodically superseded by faster or more effective equivalents having substantially the same function. Accordingly, alternative standards and protocols having the same or similar functions are considered equivalents thereof.
The illustrations of the embodiments described herein are intended to provide a general understanding of the various embodiments. These illustrations are not intended to serve as a complete description of all of the elements and features of apparatus and systems that utilize the structures or methods described herein. Many other embodiments may be apparent to those of skill in the art upon review of this disclosure. Other embodiments may be utilized and derived from the disclosure, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. Moreover, these illustrations are merely representational and may not be drawn to scale. Some proportions in the illustrations may be exaggerated, while other proportions may be minimized. Accordingly, the disclosure and figures are to be regarded as illustrative rather than restrictive.
One or more embodiments of the present disclosure may be referred to herein, individually and/or collectively, by the term "application" merely for convenience and without intending to voluntarily limit the scope of this application to any particular application or inventive concept. Furthermore, although specific embodiments have been illustrated and described herein, it should be appreciated that any subsequent device designed to achieve the same or similar purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all subsequent adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the description.
The Abstract of the disclosure is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. Furthermore, in the foregoing detailed description, various features may be grouped together or described in a single embodiment for the purpose of streamlining the disclosure. This disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter may be directed to less than all of the features of any of the disclosed embodiments. The following claims are, therefore, to be read in this detailed description, with each claim standing on its own as defining separately claimed subject matter.
The above-disclosed subject matter is to be considered illustrative, and not restrictive, and the appended claims are intended to cover all such modifications, enhancements, and other embodiments, which fall within the true spirit and scope of the present disclosure. Accordingly, to the maximum extent allowed by law, the scope of the present disclosure is to be determined by the broadest permissible interpretation of the following claims and their equivalents, and shall not be restricted or limited by the foregoing detailed description.

Claims (20)

Translated fromChinese
1.一种用于报告与客户呼叫相关的指标的方法,所述方法由至少一个处理器实现,所述方法包括:1. A method for reporting metrics related to customer calls, the method being implemented by at least one processor, the method comprising:由所述至少一个处理器从第一客户接收服务请求呼叫;receiving, by the at least one processor, a service request call from a first client;由所述至少一个处理器分配单个客户服务代理以处理由所述第一客户发送的所述服务请求呼叫;assigning, by said at least one processor, a single customer service agent to handle said service request call sent by said first customer;由所述至少一个处理器确定将由所述单个客户服务代理用来响应所述服务请求呼叫的多个软件应用,所述服务请求呼叫包括不同类型的多个请求,其中,所述多个软件应用解决所述服务请求呼叫中包括的所述多个请求;determining, by the at least one processor, a plurality of software applications to be used by the single customer service agent to respond to the service request call, the service request call including a plurality of requests of different types, wherein the plurality of software applications resolve the plurality of requests included in the service request call;由所述至少一个处理器监控所述服务请求呼叫,以便获得与所述服务请求呼叫的时间、所述服务请求呼叫期间出现的事件、以及所述多个软件应用的至少一个输出相关的信息;monitoring, by the at least one processor, the service request call to obtain information related to a time of the service request call, an event occurring during the service request call, and at least one output of the plurality of software applications;当所述服务请求呼叫完成时,针对所述单个客户服务代理在所述服务请求呼叫期间服务所述第一客户时所使用的所述多个软件应用中的每一个软件应用,由所述至少一个处理器基于作为所述监控的结果而获得的信息来确定相应软件应用的至少一个呼叫专用指标;以及when the service request call is completed, determining, by the at least one processor, for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call, at least one call-specific metric for the corresponding software application based on information obtained as a result of the monitoring; and由所述至少一个处理器,针对所述单个客户服务代理在所述服务请求呼叫期间服务所述第一客户时所使用的所述多个软件应用中的每一个软件应用,向中心数据库报告所确定的至少一个呼叫专用指标。The determined at least one call-specific metric is reported, by the at least one processor, to a central database for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call.2.根据权利要求1所述的方法,其中,所述至少一个呼叫专用指标包括以下中的至少一个:保持时间、通话时间、平均处理时间、呼叫意图、呼叫处理、应答速度、挂断的呼叫数量、掉话数量、处理的呼叫数量、平均呼叫后工作时间、保持的呼叫百分比、保持的呼叫平均持续时间、平均时间的呼叫后工作百分比、转接的呼叫数量和百分比、会议呼叫数目和百分比、转接或会议呼叫组合百分比、服务水平百分比、转接数量、空闲时间、呼叫计数、每个团队的专业人员和团队领导在呼叫期间用于每个服务请求的服务软件应用的类型以及呼叫记录数量。2. The method of claim 1, wherein the at least one call-specific metric comprises at least one of: holding time, talk time, average handling time, call intent, call handling, answer speed, number of calls hung up, number of dropped calls, number of calls handled, average after-call work time, percentage of calls held, average duration of calls held, percentage of after-call work of average time, number and percentage of transferred calls, number and percentage of conference calls, percentage of combined transferred or conference calls, service level percentage, number of transfers, idle time, call count, type of service software application used by professionals and team leaders of each team for each service request during the call, and number of call records.3.根据权利要求1所述的方法,还包括:3. The method according to claim 1, further comprising:识别被分配来处理所述服务请求呼叫的所述客户服务代理,以及identifying the customer service agent assigned to handle the service request call, and基于所确定的至少一个呼叫专用指标和先前存储的代理专用指标数据来计算至少一个代理专用指标。At least one agent-specific metric is calculated based on the determined at least one call-specific metric and previously stored agent-specific metric data.4.根据权利要求3所述的方法,还包括:4. The method according to claim 3, further comprising:捕获与所述服务请求呼叫相关的至少一个元数据项,capturing at least one metadata item associated with the service request call,其中,所述至少一个元数据项包括以下中的至少一个:电话数据、与所识别的代理相关的用户档案数据、由所述单个客户服务代理所使用的所述多个软件应用中的每一个软件应用的标识、以及与所识别的代理是否在所述服务请求呼叫期间执行过搜索功能相关的信息。Wherein, the at least one metadata item includes at least one of: telephone data, user profile data associated with the identified agent, an identification of each of the multiple software applications used by the single customer service agent, and information related to whether the identified agent performed a search function during the service request call.5.根据权利要求3所述的方法,还包括:5. The method according to claim 3, further comprising:在与所识别的客户服务代理相关联的显示器上显示用户界面,所述用户界面包括与所述服务请求呼叫相关的信息和与对应于所述第一客户的历史交互序列相关的信息。A user interface is displayed on a display associated with the identified customer service agent, the user interface including information related to the service request call and information related to a historical sequence of interactions corresponding to the first customer.6.根据权利要求1所述的方法,其中,所述多个软件应用包括:6. The method of claim 1, wherein the plurality of software applications comprises:可用于响应所述服务请求呼叫的第一方面的第一软件应用,和至少a first software application operable to respond to the first aspect of the service request call, and at least可用于响应所述服务请求呼叫的第二方面的第二软件应用。A second software application may be used to respond to a second aspect of the service request call.7.根据权利要求6所述的方法,其中,所述至少一个呼叫专用指标包括:7. The method according to claim 6, wherein the at least one call-specific indicator comprises:与所述服务请求呼叫的第一方面相关的第一呼叫专用指标,和至少a first call-specific indicator associated with a first aspect of the service request call, and at least与所述服务请求呼叫的第二方面相关的第二呼叫专用指标。A second call-specific indicator related to a second aspect of the service request call.8.根据权利要求1所述的方法,还包括:8. The method according to claim 1, further comprising:使用容器软件应用来进行所述监控和所述报告,所述容器软件应用被设计为便于所述多个软件应用中的各个软件应用之间的交互。The monitoring and the reporting are performed using a container software application designed to facilitate interaction between individual software applications of the plurality of software applications.9.一种用于报告与客户呼叫相关的指标的计算装置,所述计算装置包括:9. A computing device for reporting metrics related to customer calls, the computing device comprising:处理器;processor;存储器;以及Memory; and通信接口,耦合到处理器和存储器中的每一个,a communication interface coupled to each of the processor and the memory,其中,所述处理器被配置为:Wherein, the processor is configured to:经由所述通信接口接收来自第一客户的服务请求呼叫;receiving a service request call from a first customer via the communication interface;分配单个客户服务代理来处理由所述第一客户发送的所述服务请求呼叫;assigning a single customer service agent to handle the service request call sent by the first customer;确定将由所述单个客户服务代理用来响应所述服务请求呼叫的多个软件应用,所述服务请求呼叫包括不同类型的多个请求,其中,所述多个软件应用解决所述服务请求呼叫中包括的所述多个请求;determining a plurality of software applications to be used by the single customer service agent to respond to the service request call, the service request call including a plurality of requests of different types, wherein the plurality of software applications resolve the plurality of requests included in the service request call;监控所述服务请求呼叫,以便获得与所述服务请求呼叫的时间、所述服务请求呼叫期间出现的事件、以及所述多个软件应用的至少一个输出相关的信息;monitoring the service request call to obtain information related to a time of the service request call, an event occurring during the service request call, and at least one output of the plurality of software applications;当所述服务请求呼叫完成时,针对所述单个客户服务代理在所述服务请求呼叫期间服务所述第一客户时所使用的所述多个软件应用中的每一个软件应用,基于作为所述监控的结果而获得的信息来确定相应软件应用的至少一个呼叫专用指标;以及when the service request call is completed, determining, for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call, at least one call-specific metric for the corresponding software application based on information obtained as a result of the monitoring; and针对所述单个客户服务代理在所述服务请求呼叫期间服务所述第一客户时所使用的所述多个软件应用中的每一个软件应用,向中心数据库报告所确定的至少一个呼叫专用指标。The determined at least one call-specific metric is reported to a central database for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call.10.根据权利要求9所述的计算装置,其中,所述至少一个呼叫专用指标包括以下中的至少一个:保持时间、通话时间、平均处理时间、呼叫意图、呼叫处理、应答速度、挂断的呼叫数量、掉话数量、处理的呼叫数量、平均呼叫后工作时间、保持的呼叫百分比、保持的呼叫平均持续时间、平均时间的呼叫后工作百分比、转接的呼叫数量和百分比、会议呼叫数目和百分比、转接或会议呼叫组合百分比、服务水平百分比、转接数量、空闲时间、呼叫计数、每个团队的专业人员和团队领导在呼叫期间用于每个服务请求的服务软件应用的类型以及呼叫记录数量。10. The computing device of claim 9, wherein the at least one call-specific metric comprises at least one of: hold time, talk time, average handling time, call intent, call handling, answer speed, number of calls hung up, number of dropped calls, number of calls handled, average after-call work time, percentage of calls held, average duration of calls held, percentage of after-call work of average time, number and percentage of calls transferred, number and percentage of conference calls, percentage of combined transferred or conference calls, service level percentage, number of transfers, idle time, call count, type of service software application used by professionals and team leaders of each team for each service request during a call, and number of call records.11.根据权利要求9所述的计算装置,其中,所述处理器还被配置为:11. The computing device of claim 9, wherein the processor is further configured to:识别被分配来处理所述服务请求呼叫的所述客户服务代理,并identifying the customer service agent assigned to handle the service request call, and基于所确定的至少一个呼叫专用指标和先前存储的代理专用指标数据来计算至少一个代理专用指标。At least one agent-specific metric is calculated based on the determined at least one call-specific metric and previously stored agent-specific metric data.12.根据权利要求11所述的计算装置,其中,所述处理器还被配置为:12. The computing device of claim 11, wherein the processor is further configured to:捕获与所述服务请求呼叫相关的至少一个元数据项,以及capturing at least one metadata item associated with the service request call, and其中,所述至少一个元数据项包括以下中的至少一个:电话数据、与所识别的代理相关的用户档案数据、由所述单个客户服务代理所使用的所述多个软件应用中的每一个软件应用的标识、以及与所识别的代理是否在所述服务请求呼叫期间执行过搜索功能相关的信息。Wherein, the at least one metadata item includes at least one of: telephone data, user profile data associated with the identified agent, an identification of each of the multiple software applications used by the single customer service agent, and information related to whether the identified agent performed a search function during the service request call.13.根据权利要求11所述的计算装置,其中,所述处理器还被配置为:13. The computing device of claim 11, wherein the processor is further configured to:在与所识别的客户服务代理相关联的显示器上显示用户界面,所述用户界面包括与所述服务请求呼叫相关的信息和与对应于所述第一客户的历史交互序列相关的信息。A user interface is displayed on a display associated with the identified customer service agent, the user interface including information related to the service request call and information related to a historical sequence of interactions corresponding to the first customer.14.根据权利要求9所述的计算装置,其中,所述多个软件应用包括:14. The computing device of claim 9, wherein the plurality of software applications comprises:可用于响应所述服务请求呼叫的第一方面的第一软件应用,和至少a first software application operable to respond to the first aspect of the service request call, and at least可用于响应所述服务请求呼叫的第二方面的第二软件应用。A second software application may be used to respond to a second aspect of the service request call.15.根据权利要求14所述的计算装置,其中,所述至少一个呼叫专用指标包括:15. The computing device of claim 14, wherein the at least one call-specific indicator comprises:与所述服务请求呼叫的第一方面相关的第一呼叫专用指标;和至少a first call-specific indicator associated with a first aspect of said service request call; and at least与所述服务请求呼叫的第二方面相关的第二呼叫专用指标。A second call-specific indicator related to a second aspect of the service request call.16.根据权利要求9所述的计算装置,其中,所述处理器还被配置为:16. The computing device of claim 9, wherein the processor is further configured to:使用容器软件应用来进行所述监控和所述报告,所述容器软件应用被设计为便于所述多个软件应用中的各个软件应用之间的交互。The monitoring and the reporting are performed using a container software application designed to facilitate interaction between individual software applications of the plurality of software applications.17.一种非暂时性计算机可读存储介质,其存储用于报告与客户呼叫相关的指标的指令,所述存储介质包括可执行代码,所述可执行代码在由处理器执行时使所述处理器:17. A non-transitory computer readable storage medium storing instructions for reporting metrics related to customer calls, the storage medium comprising executable code that, when executed by a processor, causes the processor to:从第一客户接收服务请求呼叫;receiving a service request call from a first customer;分配单个客户服务代理来处理由所述第一客户发送的所述服务请求呼叫;assigning a single customer service agent to handle the service request call sent by the first customer;确定将由所述单个客户服务代理用来响应所述服务请求呼叫的多个软件应用,所述服务请求呼叫包括不同类型的多个请求,其中,所述多个软件应用解决所述服务请求呼叫中包括的所述多个请求;determining a plurality of software applications to be used by the single customer service agent to respond to the service request call, the service request call including a plurality of requests of different types, wherein the plurality of software applications resolve the plurality of requests included in the service request call;监控所述服务请求呼叫,以便获得与所述服务请求呼叫的时间、所述服务请求呼叫期间出现的事件、以及所述多个软件应用的至少一个输出相关的信息;monitoring the service request call to obtain information related to a time of the service request call, an event occurring during the service request call, and at least one output of the plurality of software applications;当所述服务请求呼叫完成时,针对所述单个客户服务代理在所述服务请求呼叫期间服务所述第一客户时所使用的所述多个软件应用中的每一个软件应用,基于所述监控的结果来确定相应软件应用的至少一个呼叫专用指标;以及When the service request call is completed, for each of the plurality of software applications used by the single customer service agent in serving the first customer during the service request call, determining at least one call-specific metric for the corresponding software application based on the monitoring results; and针对所述单个客户服务代理在所述服务请求呼叫期间服务所述第一客户时所使用的所述多个软件应用中的每一个软件应用,向中心数据库报告所确定的至少一个呼叫专用指标。The determined at least one call-specific metric is reported to a central database for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call.18.根据权利要求17所述的存储介质,其中,所述可执行代码还被配置为使所述处理器:18. The storage medium of claim 17, wherein the executable code is further configured to cause the processor to:识别被分配来处理所述服务请求呼叫的所述客户服务代理,并identifying the customer service agent assigned to handle the service request call, and基于所确定的至少一个呼叫专用指标和先前存储的代理专用指标数据来计算至少一个代理专用指标。At least one agent-specific metric is calculated based on the determined at least one call-specific metric and previously stored agent-specific metric data.19.根据权利要求18所述的存储介质,其中,所述可执行代码还被配置为使处理器:19. The storage medium of claim 18, wherein the executable code is further configured to cause the processor to:在与所识别的客户服务代理相关联的显示器上显示用户界面,所述用户界面包括与所述服务请求呼叫相关的信息和与对应于所述第一客户的历史交互序列相关的信息。A user interface is displayed on a display associated with the identified customer service agent, the user interface including information related to the service request call and information related to a historical sequence of interactions corresponding to the first customer.20.根据权利要求17所述的存储介质,其中,所述多个软件应用包括:20. The storage medium of claim 17, wherein the plurality of software applications comprises:可用于响应所述服务请求呼叫的第一方面的第一软件应用;和至少可用于响应所述服务请求呼叫的第二方面的第二软件应用。a first software application operable to respond to a first aspect of the service request call; and a second software application operable to respond to at least a second aspect of the service request call.
CN202280047104.0A2021-06-302022-05-25 Method and system for real-time reporting of metrics to replaceable agents in a full-spectrum contact centerActiveCN117597911B (en)

Applications Claiming Priority (3)

Application NumberPriority DateFiling DateTitle
US17/363,9842021-06-30
US17/363,984US11558508B1 (en)2021-06-302021-06-30Method and system for real time reporting of metrics to fungible agents in omnichannel contact center
PCT/US2022/030911WO2023278076A1 (en)2021-06-302022-05-25Method and system for real time reporting of metrics to fungible agents in omnichannel contact center

Publications (2)

Publication NumberPublication Date
CN117597911A CN117597911A (en)2024-02-23
CN117597911Btrue CN117597911B (en)2025-02-18

Family

ID=84692930

Family Applications (1)

Application NumberTitlePriority DateFiling Date
CN202280047104.0AActiveCN117597911B (en)2021-06-302022-05-25 Method and system for real-time reporting of metrics to replaceable agents in a full-spectrum contact center

Country Status (5)

CountryLink
US (1)US11558508B1 (en)
EP (1)EP4364394B1 (en)
JP (1)JP7696023B2 (en)
CN (1)CN117597911B (en)
WO (1)WO2023278076A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
US20250173164A1 (en)*2023-11-272025-05-29Wells Fargo Bank, N.A.Omni-channel micro frontend control plane

Citations (1)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
WO2020251987A1 (en)*2019-06-102020-12-17Greeneden U.S. Holdings Ii, Llc.System and method for adding content to contact center interactions

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
US8917854B2 (en)*2013-01-082014-12-23Xerox CorporationSystem to support contextualized definitions of competitions in call centers
US20160079207A1 (en)*2013-04-232016-03-17PS4 Luxco S.a.r..L.Semiconductor device and method for manufacturing same
US9813558B1 (en)*2014-04-112017-11-07United Services Automobile Association (Usaa)Systems and methods relating to caller-centric call data
US20160125652A1 (en)*2014-11-032016-05-05Avaya Inc.Augmented reality supervisor display
US20170111503A1 (en)*2015-10-192017-04-20Genesys Telecommunications Laboratories, Inc.Optimized routing of interactions to contact center agents based on agent preferences
US10498859B2 (en)*2017-04-062019-12-03Genesys Telecommunications Laboratories, Inc.System and method for self-deploying and self-adapting contact center components
US20190082051A1 (en)*2017-09-132019-03-14Teleperformance SeDynamic computing environment allocation for contact center interaction
JP2021044735A (en)2019-09-122021-03-18第一生命保険株式会社Server device, program of server device, and information processing system
US11089162B1 (en)*2020-05-282021-08-10Nice Ltd.Dynamic metric optimization in predictive behavioral routing

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
WO2020251987A1 (en)*2019-06-102020-12-17Greeneden U.S. Holdings Ii, Llc.System and method for adding content to contact center interactions

Also Published As

Publication numberPublication date
US11558508B1 (en)2023-01-17
EP4364394A1 (en)2024-05-08
JP2024529282A (en)2024-08-06
EP4364394B1 (en)2025-10-01
US20230007122A1 (en)2023-01-05
CN117597911A (en)2024-02-23
EP4364394A4 (en)2024-10-16
WO2023278076A1 (en)2023-01-05
JP7696023B2 (en)2025-06-19

Similar Documents

PublicationPublication DateTitle
US11146682B1 (en)Learning based metric determination for service sessions
US11272057B1 (en)Learning based metric determination for service sessions
CN117157628A (en) Systems and methods related to applied anomaly detection and contact center computing environments
US10931827B1 (en)Database allocation and analytics for service call centers
US9846527B2 (en)Task management from within a data feed
US20130297442A1 (en)System and method for routing and tracking real estate leads
CN108476230A (en) Optimal Routing of Interactions to Contact Center Agents Based on Machine Learning
CN105960655A (en)System and method for performance-based routing of interactions in a contact center
US10019680B2 (en)System and method for distributed rule-based sequencing engine
JP7538114B2 (en) How inbound interactions are routed
US20180165767A1 (en)System and method utilizing threshold priority values for a risk relationship management platform
US12050897B2 (en)Controlled rollouts for frontend assets
US20150350444A1 (en)Methods and systems for providing a multi-channel customer engagement experience
CN117597911B (en) Method and system for real-time reporting of metrics to replaceable agents in a full-spectrum contact center
US11114087B1 (en)Automated digital conversation manager
US20170134580A1 (en)Enhanced quality monitoring
US10176459B2 (en)Sending an out-of-facility notification based on aggregated content from a task management system and communications with at least one collaboration partner in an occupation context
CN113283814A (en)Business processing efficiency determination method and device, electronic equipment and readable storage medium
US10757263B1 (en)Dynamic resource allocation
US20230073930A1 (en)A system and method for adaptive cloud conversation platform
US10044823B2 (en)Social content aggregation
US20230222044A1 (en)System and method for automatically monitoring performance of software robots
CN113722449A (en)Information processing method, device, electronic equipment and computer readable medium
CN115312208A (en)Method, device, equipment and medium for displaying treatment data
JP2020113179A (en)Transaction monitoring system, information monitoring system, control method of transaction monitoring system, and program

Legal Events

DateCodeTitleDescription
PB01Publication
PB01Publication
SE01Entry into force of request for substantive examination
SE01Entry into force of request for substantive examination
GR01Patent grant
GR01Patent grant

[8]ページ先頭

©2009-2025 Movatter.jp